Quality Assurance in Survey Data: Frameworks, Tools, and Quality Indicators |
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| Coordinator 1 | Mr Thomas Knopf (GESIS- Leibniz Institute for the Social Sciences ) |
| Coordinator 2 | Mrs Fabienne Krämer (GESIS- Leibniz Institute for the Social Sciences ) |
| Coordinator 3 | Dr Jessica Daikeler (GESIS- Leibniz Institute for the Social Sciences ) |
Survey data, collected through various modes such as online surveys, face-to-face interviews, and telephone surveys, is subject to a wide range of potential errors that can compromise data integrity. Addressing these challenges requires robust frameworks, advanced tools, and reliable quality indicators to manage, validate, and enhance survey data quality.
This session will focus on the key aspects of quality assurance in survey data collection and analysis, with a particular emphasis on the development and application of data quality indicators. We invite contributions that suggest and showcase quality indicators, designed to maintain the integrity and usability of survey data. Key topics will include:
1. Frameworks for Quality Assurance: An overview of frameworks developed to assess the quality of survey data.
2. Tools and Platforms for Data Validation: A discussion on tools and technologies aimed at validating or improving the quality of survey data as well as platforms tailored to combine tools, such as the KODAQS toolbox.
3. Data quality indicators: We seek contributions that demonstrate effective use of quality indicators like response bias indicators or data consistency checks in real-world case studies, showcasing how they address and enhance data quality.
4. Didactics of Data Quality Issues: Approaches to teaching and promoting data quality assurance for survey data. This section will explore educational strategies to equip researchers and practitioners with the necessary skills to effectively tackle data quality issues.